[Version] v3.0.0b10 (#591)

* [Version] v3.0.0b10

* Update test_replay_trajectory.py

docs/source/_static/version_switcher.json

@@ -4,9 +4,9 @@
     "url": "https://maniskill.readthedocs.io/en/latest/"
   },
   {
-    "name": "3.0.0b9 (stable)",
-    "version": "v3.0.0b9",
-    "url": "https://maniskill.readthedocs.io/en/v3.0.0b9/",
+    "name": "3.0.0b10 (stable)",
+    "version": "v3.0.0b10",
+    "url": "https://maniskill.readthedocs.io/en/v3.0.0b10/",
     "preferred": true
   }
 ]

examples/baselines/tdmpc2/environment.yaml

@@ -47,7 +47,7 @@ dependencies:
     - tqdm==4.66.1
     - wandb==0.16.2
     - wheel==0.38.0
-    - mani_skill>=3.0.0b9
+    - mani_skill>=3.0.0b10
     ####################
     # Gym:
     # (unmaintained but required for maniskill2/meta-world/myosuite)

mani_skill/__init__.py

@@ -3,7 +3,7 @@
 
 from .utils.logging_utils import logger
 
-__version__ = "3.0.0b9"
+__version__ = "3.0.0b10"
 
 # ---------------------------------------------------------------------------- #
 # Setup paths

mani_skill/envs/sapien_env.py

@@ -813,7 +813,11 @@ def reset(self, seed=None, options=None):
             self.scene._gpu_fetch_all()
 
         # we reset controllers here because some controllers depend on the agent/articulation qpos/poses
-        self.agent.controller.reset()
+        if isinstance(self.agent.controller, dict):
+            for controller in self.agent.controller.values():
+                controller.reset()
+        else:
+            self.agent.controller.reset()
 
         obs = self.get_obs()
 

setup.py

@@ -1,13 +1,14 @@
 from setuptools import find_packages, setup
 
-__version__ = "3.0.0b9"
+__version__ = "3.0.0b10"
 
-long_description = """ManiSkill is a powerful unified framework for robot simulation and training powered by [SAPIEN](https://sapien.ucsd.edu/). The entire stack is as open-source as possible and ManiSkill v3 is in beta release now. Among its features include:
-- GPU parallelized visual data collection system. On the high end you can collect RGBD + Segmentation data at 20k FPS with a 4090 GPU, 10-100x faster compared to most other simulators.
-- Example tasks covering a wide range of different robot embodiments (quadruped, mobile manipulators, single-arm robots) as well as a wide range of different tasks (table-top, locomotion, dextrous manipulation)
-- GPU parallelized tasks, enabling incredibly fast synthetic data collection in simulation
-- GPU parallelized tasks support simulating diverse scenes where every parallel environment has a completely different scene/set of objects
-- Flexible task building API that abstracts away much of the complex GPU memory management code
+long_description = """ManiSkill is a powerful unified framework for robot simulation and training powered by [SAPIEN](https://sapien.ucsd.edu/), with a strong focus on manipulation skills. The entire tech stack is as open-source as possible and ManiSkill v3 is in beta release now. Among its features include:
+- GPU parallelized visual data collection system. On the high end you can collect RGBD + Segmentation data at 30,000+ FPS with a 4090 GPU, 10-1000x faster compared to most other simulators.
+- GPU parallelized simulation, enabling high throughput state-based synthetic data collection in simulation
+- GPU parallelized heteogeneous simuluation, where every parallel environment has a completely different scene/set of objects
+- Example tasks cover a wide range of different robot embodiments (humanoids, mobile manipulators, single-arm robots) as well as a wide range of different tasks (table-top, drawing/cleaning, dextrous manipulation)
+- Flexible and simple task building API that abstracts away much of the complex GPU memory management code via an object oriented design
+- Real2sim environments for scalably evaluating real-world policies 60-100x faster via GPU simulation.
 
 Please refer our [documentation](https://maniskill.readthedocs.io/en/latest) to learn more information."""
 

tests/test_replay_trajectory.py

@@ -11,7 +11,7 @@
         "pd_joint_delta_pos",
         "pd_joint_target_delta_pos",
         "pd_joint_vel",
-        # "pd_ee_delta_pose", # TODO (stao): This is bugged at the moment
+        "pd_ee_delta_pose",
     ],
 )
 def test_replay_trajectory(control_mode):